> ## Documentation Index
> Fetch the complete documentation index at: https://confidence-auth-testing.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Explore Experiment Results

> Learn how to create explorations to drill down into experiment results.

**Explore Experiment Results**

Learn how to create explorations to drill down into experiment results.

[Explorations](/docs/capabilities/experiments/exploration.md) let you analyze experiment results with additional metrics and dimensions for exploratory purposes.

> [!NOTE]
>
> An experiment needs to have produced exposure for an exploration to be possible.

## Create an Exploration

**1. Navigate to the experiment**

After your experiment starts to produce exposure, open the experiment and select the **Result** tab.

**2. Create a new exploration**

Click the **+** button next to the **Explorations** heading in the right sidebar.

**3. Enter a name**

In the **Create exploratory analysis** dialog, enter a name for your exploration and click **Create**.

## Add Metrics

**1. Open the metric selection dialog**

Click **Add metric** to open the metric selection dialog.

**2. Select metrics**

Use the checkboxes to select the metrics you want. You can select any metric that uses the same entity configured in the metric configuration section for your experiment.

**3. Add the metrics**

Click **Add metrics** to add the selected metrics to your exploration.

**4. Trigger calculations**

Click **Retrigger** to start the calculations for your selected metrics.

## Add Dimensions

**1. Select dimensions for each metric**

For each metric, you can add dimensions (if any exist). Dimensions come from the fact table that the metric uses and dimension tables that use the same entity as the metric.

## Write a Conclusion

After you have seen the results, you should write a conclusion detailing what you learned from this analysis.
The conclusion is important for posterity, and to help others understand what the outcome of
running the analysis was.
A good conclusion states the reason for running the analysis, the interpretation of the results,
and if you took any action based on it.

## Delete an Exploration

**1. Open the exploration**

Click the exploration in the **Explorations** sidebar section.

**2. Delete the exploration**

Click the **Delete** button and confirm the deletion.

> [!TIP]
>
> Do not delete an Exploration because results are not significant! Understanding
> that there was no effect is as important as finding an interesting effect.
> There is also a good chance that someone has the same great idea as you
> ‐ keeping your analysis around is likely to reduce duplicate efforts in
> your organization.

## Related Resources

> **[Exploration Reference](/docs/capabilities/experiments/exploration.md)**
>
> Deep dive into exploration features

> **[Create Dimension Tables](/docs/capabilities/metrics/create-dimension-table.md)**
>
> Add dimensions for segmentation

> **[Analyze Results](/docs/capabilities/experiments/analyze-results.md)**
>
> Learn about result analysis